The effects of winter ice cover on the trophic ecology of whitefish (Coregonus lavaretus L.) in subarctic lakes

Lakes in Arctic and subarctic regions display extreme levels of seasonal variation in light, temperature and ice cover. Comparatively little is known regarding the effects of such seasonal variation on the diet and resource use of fish species inhabiting these systems. Variation in the diet of European whitefish Coregonus lavaretus (L.) during periods of ice cover in this region is often regarded as 'common knowledge'; however, this aspect of the species' ecology has not been examined empirically. Here, we outline the differences in invertebrate community structure, fish activity, and resource use of monomorphic whitefish populations between summer (August-September) and winter (February-March) in three subarctic lakes in Finnish Lapland. Benthic macroinvertebrate densities did not exhibit measurable differences between summer and winter. Zooplankton diversity and abundance, and activity levels of all fish species (measured as catch per unit effort) were lower in winter. The summer diet of C. lavaretus was typical of a generalist utilising a variety of prey sources. In winter, its dietary niche was significantly reduced, and the diet was dominated by chironomid larvae in all study sites. Pelagic productivity decreases during winter, and fish species inhabiting these systems are therefore restricted to feeding on benthic prey. Sampling time has strong effect on our understanding of resource utilisation by whitefish in subarctic lakes and should be taken into account in future studies of these systems. © 2012 John Wiley & Sons A/S.

Palaeoglacial and palaeoclimatic conditions in the NW Pacific, as revealed by a morphometric analysis of cirques upon the Kamchatka Peninsula

The distribution of glacial cirques upon the Kamchatka peninsula, Far Eastern Russia, is systematically mapped from satellite images and digital elevation model data. A total of 3,758 cirques are identified, 238 of which are occupied by active glaciers. The morphometry of the remaining 3,520 cirques is analysed. These cirques are found to show a very strong N bias in their azimuth (orientation), likely resulting from aspect-related variations in insolation. The strength of this N bias is considered to indicate that former glaciation upon the peninsula was often ‘marginal’, and mainly of cirque-type, with peaks extending little above regional equilibrium-line altitudes. This is supported by the fact that S and SE-facing cirques are the highest in the dataset, suggesting that glacier-cover was rarely sufficient to allow S and SE-facing glaciers to develop at low altitudes. The strength of these azimuth-related variations in cirque altitude is thought to reflect comparatively cloud-free conditions during former periods of glaciation. It is suggested that these characteristics, of marginal glaciation and comparatively cloud-free conditions, reflect the region’s former aridity, which was likely intensified at the global Last Glacial Maximum, and during earlier periods of ice advance, as a result of the development of negative pressure anomalies over the North Pacific (driven by the growth of the Laurentide Ice Sheet), combined with other factors, including an increase in the extent and duration of sea ice, a reduction in global sea levels, cooler sea surface temperatures, and the localised growth of mountain glaciers. There is published evidence to suggest extensive glaciation of the Kamchatka Peninsula at times during the Late Quaternary, yet the data presented here appears to suggest that such phases were comparatively short-lived, and that smaller cirque-type glaciers were generally more characteristic of the period.

Palynological perspectives on vegetation survey: a critical step for model-based reconstruction of Quaternary land cover

1. Quantitative reconstruction of past vegetation distribution and abundance from sedimentary pollen records provides an important baseline for understanding long term ecosystem dynamics and for the calibration of earth system process models such as regional-scale climate models, widely used to predict future environmental change. Most current approaches assume that the amount of pollen produced by each vegetation type, usually expressed as a relative pollen productivity term, is constant in space and time.
2. Estimates of relative pollen productivity can be extracted from extended R-value analysis (Parsons and Prentice, 1981) using comparisons between pollen assemblages deposited into sedimentary contexts, such as moss polsters, and measurements of the present day vegetation cover around the sampled location. Vegetation survey method has been shown to have a profound effect on estimates of model parameters (Bunting and Hjelle, 2010), therefore a standard method is an essential pre-requisite for testing some of the key assumptions of pollen-based reconstruction of past vegetation; such as the assumption that relative pollen productivity is effectively constant in space and time within a region or biome.
3. This paper systematically reviews the assumptions and methodology underlying current models of pollen dispersal and deposition, and thereby identifies the key characteristics of an effective vegetation survey method for estimating relative pollen productivity in a range of landscape contexts.
4. It then presents the methodology used in a current research project, developed during a practitioner workshop. The method selected is pragmatic, designed to be replicable by different research groups, usable in a wide range of habitats, and requiring minimum effort to collect adequate data for model calibration rather than representing some ideal or required approach. Using this common methodology will allow project members to collect multiple measurements of relative pollen productivity for major plant taxa from several northern European locations in order to test the assumption of uniformity of these values within the climatic range of the main taxa recorded in pollen records from the region.

The Holocene vegetation cover of Britain and Ireland: overcoming problems of scale and discerning patterns of openness

The vegetation of Europe has undergone substantial changes during the course of the Holocene epoch, resulting from range expansion of plants following climate amelioration, competition between taxa and disturbance through anthropogenic activities. Much of the detail of this pattern is understood from
decades of pollen analytical work across Europe, and this understanding has been used to address questions relating to vegetation-climate feedback, biogeography and human impact. Recent advances in modelling the relationship between pollen and vegetation now make it possible to transform pollen
proportions into estimates of vegetation cover at both regional and local spatial scales, using the Landscape Reconstruction Algorithm (LRA), i.e. the REVEALS (Regional Estimates of VEgetation Abundance from Large Sites) and the LOVE (LOcal VEgetation) models. This paper presents the compilation and analysis of 73 pollen stratigraphies from the British Isles, to assess the application of the LRA and describe the pattern of landscape/woodland openness (i.e. the cover of low herb and bushy vegetation) through the Holocene. The results show that multiple small sites can be used as an effective replacement for a single large site for the reconstruction of regional vegetation cover. The REVEALS vegetation estimates imply that the British Isles had a greater degree of landscape/woodland openness at the regional scale than areas on the European mainland. There is considerable spatial bias in the British Isles dataset towards wetland areas and uplands, which may explain higher estimates of landscape openness compared with Europe. Where multiple estimates of regional vegetation are available from within the same region inter-regional differences are greater than intra-regional differences, supporting the use of the REVEALS model to the estimation of regional vegetation from pollen data.

Spitzer Space Telescope spectra of post-AGB stars in the large magellanic Cloud-polycyclic aromatic hydrocarbons at low metallicities

This paper reports variations of polycyclic aromatic hydrocarbons (PAHs) features that were found in Spitzer Space Telescope spectra of carbon-rich post-asymptotic giant branch (post-AGB) stars in the Large Magellanic Cloud (LMC). The paper consists of two parts. The first part describes our Spitzer spectral observing programme of 24 stars including post-AGB candidates. The latter half of this paper presents the analysis of PAH features in 20 carbon-rich post-AGB stars in the LMC, assembled from the Spitzer archive as well as from our own programme.We found that five post-AGB stars showed a broad feature with a peak at 7.7 μm, that had not been classified before. Further, the 10-13 μm PAH spectra were classified into four classes, one of which has three broad peaks at 11.3, 12.3 and 13.3 μm rather than two distinct sharp peaks at 11.3 and 12.7 μm, as commonly found in HII regions. Our studies suggest that PAHs are gradually processed while the central stars evolve from post-AGB phase to planetary nebulae, changing their composition before PAHs are incorporated into the interstellar medium. Although some metallicity dependence of PAH spectra exists, the evolutionary state of an object is more significant than its metallicity in determining the spectral characteristics of PAHs for LMC and Galactic post-AGB stars. © 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.

The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation

Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.

Particle-in-cell simulation study of the interaction between a relativistically moving leptonic micro-cloud and ambient electrons

Context. The jets of compact accreting objects are composed of electrons and a mixture of positrons and ions. These outflows impinge on the interstellar or intergalactic medium and both plasmas interact via collisionless processes. Filamentation (beam-Weibel) instabilities give rise to the growth of strong electromagnetic fields. These fields thermalize the interpenetrating plasmas. 

Aims. Hitherto, the effects imposed by a spatial non-uniformity on filamentation instabilities have remained unexplored. We examine the interaction between spatially uniform background electrons and a minuscule cloud of electrons and positrons. The cloud size is comparable to that created in recent laboratory experiments and such clouds may exist close to internal and external shocks of leptonic jets. The purpose of our study is to determine the prevalent instabilities, their ability to generate electromagnetic fields and the mechanism, by which the lepton micro-cloud transfers energy to the background plasma. 

Methods. A square micro-cloud of equally dense electrons and positrons impinges in our particle-in-cell (PIC) simulation on a spatially uniform plasma at rest. The latter consists of electrons with a temperature of 1 keV and immobile ions. The initially charge- and current neutral micro-cloud has a temperature of 100 keV and a side length of 2.5 plasma skin depths of the micro-cloud. The side length is given in the reference frame of the background plasma. The mean speed of the micro-cloud corresponds to a relativistic factor of 15, which is relevant for laboratory experiments and for relativistic astrophysical outflows. The spatial distributions of the leptons and of the electromagnetic fields are examined at several times. 

Results. A filamentation instability develops between the magnetic field carried by the micro-cloud and the background electrons. The electromagnetic fields, which grow from noise levels, redistribute the electrons and positrons within the cloud, which boosts the peak magnetic field amplitude. The current density and the moduli of the electromagnetic fields grow aperiodically in time and steadily along the direction that is anti-parallel to the cloud's velocity vector. The micro-cloud remains conjoined during the simulation. The instability induces an electrostatic wakefield in the background plasma. 

Conclusions. Relativistic clouds of leptons can generate and amplify magnetic fields even if they have a microscopic size, which implies that the underlying processes can be studied in the laboratory. The interaction of the localized magnetic field and high-energy leptons will give rise to synchrotron jitter radiation. The wakefield in the background plasma dissipates the kinetic energy of the lepton cloud. Even the fastest lepton micro-clouds can be slowed down by this collisionless mechanism. Moderately fast charge- and current neutralized lepton micro-clouds will deposit their energy close to relativistic shocks and hence they do not constitute an energy loss mechanism for the shock.

A Lightweight Tool for Anomaly Detection in Cloud Data Centres

Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting anomalies often use machine learning techniques, application instance behaviours or system metrics distribu- tion, which are complex to implement in Cloud computing environments as they require training, access to application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre- lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second (IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when an application stresses the disk, indicating a node-level anomaly.

Uncertainty in the Cloud: An Angel-Daemon Approach to Modelling Performance

Uncertainty profiles are used to study the effects of contention within cloud and service-based environments. An uncertainty profile provides a qualitative description of an environment whose quality of service (QoS) may fluctuate unpredictably. Uncertain environments are modelled by strategic games with two agents; a daemon is used to represent overload and high resource contention; an angel is used to represent an idealised resource allocation situation with no underlying contention. Assessments of uncertainty profiles are useful in two ways: firstly, they provide a broad understanding of how environmental stress can effect an application’s performance (and reliability); secondly, they allow the effects of introducing redundancy into a computation to be assessed

Towards Automated Data-Driven Model Creation for Cloud Computing Simulation

The increasing complexity and scale of cloud computing environments due to widespread data centre heterogeneity makes measurement-based evaluations highly difficult to achieve. Therefore the use of simulation tools to support decision making in cloud computing environments to cope with this problem is an increasing trend. However the data required in order to model cloud computing environments with an appropriate degree of accuracy is typically large, very difficult to collect without some form of automation, often not available in a suitable format and a time consuming process if done manually. In this research, an automated method for cloud computing topology definition, data collection and model creation activities is presented, within the context of a suite of tools that have been developed and integrated to support these activities.

Strength model for end cover separation failure in RC beams strengthened with near-surface mounted (NSM) FRP strips

As an alternative to externally bonded FRP reinforcement, near-surface mounted (NSM) FRP reinforcement can be used to effectively improve the flexural performance of RC beams. In such FRP strengthened RC beams, end cover separation failure is one of the common failure modes. This failuremode involves the detachment of the NSM FRP reinforcement together with the concrete cover along the level of the tension steel reinforcement. This paper presents a new strength model for end cover separation failure in RC beams strengthened in flexure with NSM FRP strips (i.e. rectangular FRP bars with asectional height-to-thickness ratio not less than 5), which was formulated on the basis of extensive numerical results from a parametric study undertaken using an efficient finite element approach. The proposed strength model consists of an approximate equation for the debonding strain of the FRP reinforcement at the critical cracked section and a conventional section analysis to relate this debondingstrain to the moment acting on the same section (i.e. the debonding strain). Once the debonding strain is known, the load level at end cover separation of an FRP-strengthened RC beam can be easily determined for a given load distribution. Predictions from the proposed strength model are compared with those of two existing strength models of the same type and available test results, which shows that the proposed strength model is in close agreement with test results and is far more accurate than the existing strength models.